Putting pleiotropy and selection into context defines a new paradigm for interpreting genetic data.
Putting pleiotropy and selection into context defines a new paradigm for interpreting genetic data.
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DOI:
10.1161/circgenetics.113.000126
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发表时间:
2013-06
期刊:
影响因子:
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通讯作者:
Williams SM
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文献类型:
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作者:
Predazzi IM;Rokas A;Deinard A;Schnetz-Boutaud N;Williams ND;Bush WS;Tacconelli A;Friedrich K;Fazio S;Novelli G;Haines JL;Sirugo G;Williams SM
Natural selection shapes many human genes, including some related to complex diseases. Understanding how selection affects genes, especially pleiotropic ones, may be important in evaluating disease associations and the role played by environmental variation. This may be of particular interest for genes with antagonistic roles that cause divergent patterns of selection. The lectin like low-density lipoprotein 1 receptor (LOX-1), encoded by OLR1, is exemplary. It has antagonistic functions in the cardiovascular and immune systems as the same protein domain binds oxidized LDL and bacterial cell wall proteins - the former contributing to atherosclerosis, the latter presumably protecting from infection. We studied patterns of selection in this gene, in humans and non-human primates, to determine whether variable selection can lead to conflicting results in CVD association studies. We analyzed sequences from 11 non-human primate species as well as SNP and sequence data from multiple human populations. Results indicate that the derived allele is favored across primate lineages (probably due to recent positive selection). However, both the derived and ancestral alleles were maintained in human populations, especially European ones (possibly due to balancing selection derived from LOX-1's dual roles). Balancing selection likely reflects response to diverse environmental pressures among humans. These data indicate that differential selection patterns, within and between species, in OLR1 render association studies difficult to replicate even if the gene is etiologically connected to CVD. Selection analyses can identify genes exhibiting gene-environment interactions critical for unraveling disease association.